In situ screening of quality traits in
tomato cultivars using the handheld
The development of tomato varieties with altered nutritional profiles requires efficient selection and scientific competence to measure metabolite contents in thousands of samples. Field-based devices can streamline quality assurance and Fourier-transform infrared (FTIR) techniques combined with chemometrics offer tomato processors and breeders powerful tools for the rapid assessment of tomato quality attributes.
Portable IR units enable the food manufacturer to quickly assess the quality of the product, allowing for timely correction measures during manufacture. Portable systems are simple to use and require minimal or no sample preparation. They reduce assay time and help to streamline the analytical procedure so that it is more applicable to higher sample throughput and automation, providing in-situ assessment of the sample’s composition.
This application note evaluates the performance of the novel Agilent 4200 FlexScan portable infrared units against a benchtop IR spectrometer for the determination of tomato quality parameters (Brix, pH, titratable acidity, glucose, fructose and citric acid).
Models were constructed on both spectrometers using partial least squares regression (PLSR) to predict these quality parameters, using reference data collected by traditional refractometer and chromatography methods.
The 4200 FlexScan demonstrated comparable performance to the benchtop spectrometer for the measurement of these key quality parameters, with the added advantage of delivering that information to food scientists in the field, providing increased efficiency and efficacy in assuring the quality of the end food product.
Aliquots (0.5 mL) from thawed tomato juice samples were centrifuged at 12,000 rpm for 5 minutes at 25 °C, and two drops were applied to the surface of the ATR crystal for spectral data collection. The absorbance spectra of the room temperature samples consist of 64 co-added interferograms at 4 cm-1 resolution measured in the 4000 to 600 cm-1 mid-IR wavelength range. The spectrum of each individual sample, which took less than 2 minutes to acquire, was corrected against a background spectrum of air. Duplicate independent measurements were taken on each sample and background spectra were collected after every sample to account for environmental variations. Between measurements, the ATR surface was cleaned with a 70% ethanol solution.
The spectra of 160 (80 varieties, 2 replicate spectra per variety) juice samples appeared quite homogeneous upon visual inspection, and no outliers were identified.
The major absorbance bands at approximately 3300 and 1635 cm-1 (Figure 1A) arise from water in the samples and are consistent with those reported for other fruits and vegetables. The 1800–1000 cm-1 fingerprint region exhibited peaks corresponding to the carbonyl stretching groups (1726 cm-1), C=C stretching of ring vibration (1605 cm-1, 1509 cm-1), O-H deformation (1365 cm-1) and C-OH stretching (1262 cm-1, 1145 cm-1, 1035 cm-1) associated to sugars and acids.
Second derivative mathematical transformation of the spectra helps to resolve overlapping bands and eliminates the need for baseline correction, since the most significant offset and linear baseline errors are removed.
PLSR analysis was used to generate models that are linear combinations of these spectral frequencies that correlate to the concentrations of analytes in the tomatoes that were determined using the reference analysis methods.
Screening of quality parameters in tomatoes has been accomplished through the use of the handheld Agilent 4200 FlexScan FTIR spectrometer in the mid-infrared spectral region. A simple, quick and reliable technique was developed for the determination of key analytes and the results were comparable to those obtained with a benchtop unit. The ease of use, convenience and ruggedness offered by the handheld infrared spectrometer make it an ideal tool for food scientists and technicians to obtain vital information in the field.
This tool can play a vital role in crop and process improvement studies, thus improving the quality assurance of the end food product.
Excerpt from Agilent Technologies Application Note 5991-0003EN